Comparisons of NMR spectral quality and success in crystallization demonstrate that NMR and X-ray crystallography are complementary methods for small protein structure determination

X-ray crystallography and NMR spectroscopy provide the only sources of experimental data from which protein structures can be analyzed at high or even atomic resolution. The degree to which these methods complement each other as sources of structural knowledge is a matter of debate; it is often proposed that small proteins yielding high quality, readily analyzed NMR spectra are a subset of those that readily yield strongly diffracting crystals. We have examined the correlation between NMR spectral quality and success in structure determination by X-ray crystallography for 159 prokaryotic and eukaryotic proteins, prescreened to avoid proteins providing polydisperse and/or aggregated samples. This study demonstrates that, across this protein sample set, the quality of a protein's [15N-1H]-heteronuclear correlation (HSQC) spectrum recorded under conditions generally suitable for 3D structure determination by NMR, a key predictor of the ability to determine a structure by NMR, is not correlated with successful crystallization and structure determination by X-ray crystallography. These results, together with similar results of an independent study presented in the accompanying paper (Yee, et al., J. Am. Chem. Soc., accompanying paper), demonstrate that X-ray crystallography and NMR often provide complementary sources of structural data and that both methods are required in order to optimize success for as many targets as possible in large-scale structural proteomics efforts.     

Electrochemical and chemical polymerization of acrylamide

The electrochemical and chemical polymerization of acrylamide (AA) has been studied. The electrolysis of the monomer in N,N-dimethylformamide (DMF) containing (C₄H₉)₄NClO₄ as the supporting electrolyte leads to polymer formation in both anode and cathode compartments. The cathodic polymer dissolves in the reaction mixture and the anodic polymer precipitates during the course of polymerization. A plausible mechanism for the anodic and cathodic initiation reaction has been given. The chemical polymerization of acrylamide that has been initiated by HClO₄ is analogous to its anodic polymerization. The polymer yield increases with an increase in concentration of the monomer and HClO₄. Raising the reaction temperature also enhances the polymerization rate. The overall apparent activation energy of the polymerization was determined to be ca. 19 kcal/mole. The copolymerization of acrylamide was carried out with methyl methacrylate (MMA) in a solution of HClO₄ in DMF. The reactivity ratios are r₁ (AA) = 0.25 and r₂ = 2.50. The polymerization with HClO₄ appears to be by a free radical mechanism. When the polymerization of acrylamide is carried out with HClO₄ in H₂O, a crosslinked water-insoluble gel formation takes place.     

Incorporating fault debugging activities into software reliability models: a simulation approach

A large number of software reliability growth models have been proposed to analyse the reliability of a software application based on the failure data collected during the testing phase of the application. To ensure analytical tractability, most of these models are based on simplifying assumptions of instantaneous & perfect debugging. As a result, the estimates of the residual number of faults, failure rate, reliability, and optimal software release time obtained from these models tend to be optimistic. To obtain realistic estimates, it is desirable that the assumptions of instantaneous & perfect debugging be amended. In this paper we discuss the various policies according to which debugging may be conducted. We then describe a rate-based simulation framework to incorporate explicit debugging activities, which may be conducted according to the different debugging policies, into software reliability growth models. The simulation framework can also consider the possibility of imperfect debugging in conjunction with any of the debugging policies. Further, we also present a technique to compute the failure rate, and the reliability of the software, taking into consideration explicit debugging. An economic cost model to determine the optimal software release time in the presence of debugging activities is also described. We illustrate the potential of the simulation framework using two case studies.     

Population Balance Modeling with Coupled Agglomeration and Disintegration Processes for TiO2 Nanoparticles Formation and Experimental Validation

Particle size distribution of nanoparticles plays an important role in modelling many scientific and engineering problems. In this article, we proposed a Finite Volume Method (FVM) to model TiO₂ nanoparticles formation using population balance equations (PBEs) by incorporating the simultaneous agglomeration and disintegration processes. The superposition of the PBEs for agglomeration and disintegration with different kernels leads to a system of partial-integro differential equations, which are numerically solved by using FVM. The precipitation of TiO₂ nanoparticles in the batch reactor is studied experimentally as well as by numerical simulations based on Austin and Diemer disintegration kernels and Shear agglomeration kernel. Finally, the capability of the precipitation model is evaluated and the experimental results on particle sizes are compared with the numerical results.

     

A simulation as a service cloud middleware

Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.     

Enantioselective synthesis of spiro[4H-pyran-3,3′-oxindole] derivatives catalyzed by cinchona alkaloid thioureas: Significant water effects on the enantioselectivity

An efficient stereoselective three-component reaction for the synthesis of functionalized spiro[4H-pyran-3,3′-oxindole] derivatives was realized through an organocatalyzed domino Knoevenagel/Michael/cyclization reaction using a cinchonidine-derived thiourea as the catalyst. Using water as the additive was found to improve the product ee values significantly. Under the optimized conditions, the reactions between isatins, malononitrile, and 1,3-dicarbonyl compounds yield the desired spirooxindole products in good yields (71–92%) and moderate to high ee values (up to 87% ee).     

Hydrothermal processing of waste pine wood into industrially useful products

An ongoing major outbreak of mountain pine beetle in Western Canada has provided a clear opportunity to utilize waste pinewood as a source of renewable energy. Therefore hydrothermal processing of waste pinewood as a feedstock for bio-oil and biochar production using subcritical and supercritical water technology was carried out in semi-batch mode to investigate the effect of pressure (200–400 bar) and temperature (300–400 °C) on the yield and composition of bio-oil. The pinewood samples have very high cellulose and hemicellulose content but low ash content and are thus a formidable feedstock for bioenergy production. The optimum conditions for the hydrothermal processing of the pinewood in a tubular reactor were found to be 400 °C and 250 bars with respect to biochar and bio-oil yield based on the highest calorific value analysis. Detailed characterization of bio-oil and biochar was performed using GCMS, NMR, SEM, calorific value, and elemental analysis, respectively. The critical components of bio-oil were found to be phenols, methoxyphenols, hydroxymethyl furfural (HMF), and vanillin, whereas as compared to the raw pine wood, the biochar was considerably lower H:C and O:C ratios than those of the unprocessed pinewood. The analyses of bio-oil by means of GCMS and ¹H NMR showed that it was mainly composed of heterocyclic compounds, phenols, aldehydes and acids.